| Literature DB >> 25954351 |
Guy Divita1, Qing T Zeng1, Adi V Gundlapalli1, Scott Duvall1, Jonathan Nebeker1, Matthew H Samore1.
Abstract
An opportunity exists for meaningful concept extraction and indexing from large corpora of clinical notes in the Veterans Affairs (VA) electronic medical record. Currently available tools such as MetaMap, cTAKES and HITex do not scale up to address this big data need. Sophia, a rapid UMLS concept extraction annotator was developed to fulfill a mandate and address extraction where high throughput is needed while preserving performance. We report on the development, testing and benchmarking of Sophia against MetaMap and cTAKEs. Sophia demonstrated improved performance on recall as compared to cTAKES and MetaMap (0.71 vs 0.66 and 0.38). The overall f-score was similar to cTAKES and an improvement over MetaMap (0.53 vs 0.57 and 0.43). With regard to speed of processing records, we noted Sophia to be several fold faster than cTAKES and the scaled-out MetaMap service. Sophia offers a viable alternative for high-throughput information extraction tasks.Entities:
Mesh：
Year: 2014 PMID： 25954351 PMCID： PMC4420011
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN： 1559-4076